Fair Isaac Sponsors New Research in Data Mining and A.I.
Fair Isaac Corporation is partnering with the Jacobs School
two new UC MICRO Grant projects. The first, “Cost-Sensitive Decision Making,” involves computer science professors Charles Elkan and Gary Cottrell. Their research focuses on building software models that not only make predictions, but also make optimal decisions when possible outcomes and costs unknown. "The goal of the project is to develop data mining techniques to solve new and more difficult problems," says Elkan. "They can be used for fraud detection involving credit cards, health care spending and tax returns, and they also have applications to bankruptcy prediction and identity theft prevention."

Computer engineering professor Kenneth Kreutz-Delgado heads the second project, "Data-Pattern Discovery Methods for Very Large Data Sets." This research aims to develop intelligent software, driven by sophisticated modeling that recognizes patterns of behavior in order to detect anomalies. This statistical pattern recognition also has applications in detecting credit card fraud.